AWS r4.8xlargevsAWS r4.large

r4.8xlarge pairs 32 vCPUs with 244GB of RAM at $2.1280/hr On-Demand (about $1532/mo at 24×7). r4.large pairs 2 vCPUs with 15.3GB at $0.1330/hr (~$96/mo). r4.large is 94% cheaper per hour than r4.8xlarge ($1.9950/hr gap).

Because both instances are in the **r4 family**, the only thing that changes between them is sizing — same silicon, same architecture (Intel Xeon (x86_64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: r4.8xlarge gives you 32 vCPUs and 244GB of RAM, r4.large gives you 2 vCPUs and 15.3GB. AWS scales pricing close to linearly within a family, so picking the right size is mostly about right-sizing your workload, not getting a better deal per vCPU.

On raw price-per-performance, the two are r4.large delivers ~1346% more single-thread Sysbench score per dollar (483 vs 6985 points per $1/hr). That's the cleanest signal we have for "which one runs your workload faster per dollar," but it only matters if your workload is single-thread-bound; for parallel workloads the multi-core scores (25407 vs 1395) are what to weigh. Spot pricing flips many of these comparisons — when r4.8xlarge drops to $0.6680/hr and r4.large drops to $0.0419/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r4.8xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r4.large when it's closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). When neither side is obviously right, the cheaper hourly rate usually wins for fault-tolerant batch workloads, while the higher single-core score usually wins for latency-sensitive web traffic. The regional pricing tables linked from each instance page below show where each is currently cheapest — sometimes a >20% regional gap flips the comparison entirely.